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Background The number of patients under home mechanical ventilation is increasing worldwide. The unique nature of these patients and their complex health needs exposes home caregivers to various needs and challenges regarding different dimensions of care. Objective The present study was conducted to investigate the effect of the universal model of family-centered care on the clinical outcomes of the patient and the family. Methods This clinical trial was conducted between 2020 and 2021. A total of 60 patients under invasive mechanical ventilation was selected and divided into control (routine training that is usually given by hospital staff to families to care for patients) and intervention (comprehensive pre-discharge training program to post-discharge follow-up using the universal model of family-centered care) groups using random block design and universal model of family-centered care. Home caregivers' functional skills and burden, as well as patients' readmission and mortality rates, were compared in the two groups. Results Implementing the intervention 1 and 3 months later effectively increased home caregivers' functional skills. Moreover, a statistically significant difference was observed between the two groups in terms of the psychological burden of caregiving (P  < .001); the implementation of the intervention could highly reduce the psychological burden of caregiving in the intervention group (EF = 0.94). The hospital readmission and mortality rate in the intervention group was significantly lower than in the control group (P  = .02 and P  = .03, respectively). Conclusions Given the significant impact of the universal model of family-centered care on the clinical outcomes of the patient and the family, pre-discharge training and its post-discharge follow-up and continuity of education with an active presence of nurses, as one of the main pillars of the treatment, seems essential. [ABSTRACT FROM AUTHOR]

A machine learning model for prediction of icing on vessels and offshore structures, Spice, was recently developed by Deshpande 2023. Some variables required for the prediction of icing rates in most prediction models, including Spice, such as the spray flux, cannot be easily measured. Existing models estimate these using empirical formulations that have been heavily criticized. Most existing models are also incapable of providing the distribution of icing on the structure. The current study demonstrates a method to estimate the local wind speeds, along with spray duration, spray period, and spray flux at different locations on the surface of a moving vessel. These, along with other easily measurable values of air temperature, water temperature, and salinity, are used to predict the icing rates. The result is a model, dubbed Spice2—an upgrade of the existing Spice model—that is able to provide the icing rates and the distribution of icing on the surface of vessels and other offshore structures. The model was demonstrated with a case study of a totally enclosed lifeboat where icing rates were predicted at different locations on its surface. Successful implementation of a two-phase simulation with a coupled wind–wave domain and a moving vessel was demonstrated. Research into simplification of the currently computationally expensive method is suggested. Validation of the proposed Spice2 model against a full-scale measurement is covered in part 2 of the study. [ABSTRACT FROM AUTHOR]

A hybrid CFD–ML model for the prediction of sea spray icing, SPICE2, was developed in Part 1 of this study in Deshpande et al., 2024. The SPICE2 model is an extension of the ML model, SPICE, where some of the variables required for icing rate predictions: local wind speed, spray duration, spray period, and spray flux, are computed from CFD simulations. These, along with the air and water temperatures, and the salinity from the metocean data are used for the prediction of icing rates at different locations on a moving vessel. The existing full-scale icing measurements proved to be not detailed enough for the purpose of the verification of sea spray icing prediction models and the verification of the SPICE2 required distribution of sea spray icing data on the vessel surface in addition to the vessel design for simulation. A full-scale sea spray icing test was conducted in 2018 by Sundsbø et al. on a fully enclosed lifeboat equipped for the Goliat field in the Barents Sea. The 3D design of the same lifeboat, together with the corresponding metocean conditions and ship characteristics was used for the simulation of the vessel-specific parameters required for the verification of the icing rate and distribution prediction from the SPICE2 model against the measured distribution of sea spray icing rates on the lifeboat surface. The availability of the 3D model of this lifeboat, in addition to the fact that the icing measurements from this test were detailed enough to attempt a model verification served the purpose of validating the SPICE2 model. The icing rates measured on this lifeboat are used for the full-scale validation of the SPICE2 model that is proposed in Part 1 of this study. It was seen that the icing rates predicted by SPICE2 concurred with 9 of 13 selected locations on the lifeboat. The ones which did not showed very little deviation from the measurements. The icing rate and distribution prediction with SPICE2 were satisfactorily validated against full-scale icing measurements. This is a first attempt in modelling sea spray generation using CFD and further research into CFD for the estimation of spray flux is suggested. [ABSTRACT FROM AUTHOR]

A hybrid CFD–ML model for the prediction of sea spray icing, SPICE2, was developed in Part 1 of this study in Deshpande et al., 2024. The SPICE2 model is an extension of the ML model, SPICE, where some of the variables required for icing rate predictions: local wind speed, spray duration, spray period, and spray flux, are computed from CFD simulations. These, along with the air and water temperatures, and the salinity from the metocean data are used for the prediction of icing rates at different locations on a moving vessel. The existing full-scale icing measurements proved to be not detailed enough for the purpose of the verification of sea spray icing prediction models and the verification of the SPICE2 required distribution of sea spray icing data on the vessel surface in addition to the vessel design for simulation. A full-scale sea spray icing test was conducted in 2018 by Sundsbø et al. on a fully enclosed lifeboat equipped for the Goliat field in the Barents Sea. The 3D design of the same lifeboat, together with the corresponding metocean conditions and ship characteristics was used for the simulation of the vessel-specific parameters required for the verification of the icing rate and distribution prediction from the SPICE2 model against the measured distribution of sea spray icing rates on the lifeboat surface. The availability of the 3D model of this lifeboat, in addition to the fact that the icing measurements from this test were detailed enough to attempt a model verification served the purpose of validating the SPICE2 model. The icing rates measured on this lifeboat are used for the full-scale validation of the SPICE2 model that is proposed in Part 1 of this study. It was seen that the icing rates predicted by SPICE2 concurred with 9 of 13 selected locations on the lifeboat. The ones which did not showed very little deviation from the measurements. The icing rate and distribution prediction with SPICE2 were satisfactorily validated against full-scale icing measurements. This is a first attempt in modelling sea spray generation using CFD and further research into CFD for the estimation of spray flux is suggested.

A machine learning model for prediction of icing on vessels and offshore structures, Spice, was recently developed by Deshpande 2023. Some variables required for the prediction of icing rates in most prediction models, including Spice, such as the spray flux, cannot be easily measured. Existing models estimate these using empirical formulations that have been heavily criticized. Most existing models are also incapable of providing the distribution of icing on the structure. The current study demonstrates a method to estimate the local wind speeds, along with spray duration, spray period, and spray flux at different locations on the surface of a moving vessel. These, along with other easily measurable values of air temperature, water temperature, and salinity, are used to predict the icing rates. The result is a model, dubbed Spice2—an upgrade of the existing Spice model—that is able to provide the icing rates and the distribution of icing on the surface of vessels and other offshore structures. The model was demonstrated with a case study of a totally enclosed lifeboat where icing rates were predicted at different locations on its surface. Successful implementation of a two-phase simulation with a coupled wind–wave domain and a moving vessel was demonstrated. Research into simplification of the currently computationally expensive method is suggested. Validation of the proposed Spice2 model against a full-scale measurement is covered in part 2 of the study.

There are many kinds of cellular automata models to simulate disaster spread, but there is no general modeling method. Based on this, a universal cellular automata model for disaster propagation simulation was proposed. Firstly, by analyzing the mechanism and theoretical model of disaster spread, according to the similarity of disaster dynamic development and change process, disaster spread was divided into four parts: disaster quantity set, spatio-temporal neighborhood set, judgment rule set and updating rule set. Secondly, the cellular automata modeling method was used to recombine the four parts and construct the cellular automata parameter calculation simulation model of disaster spreading. Finally, the method proposed was used to improve the urban fire spread model of A. Ohgai, and an example was given. The results show that the model can obtain the dynamic parameters of the disaster model only by inputting the environmental data and the initial disturbance of the disaster, and can provide a general modeling method and implementation mode for a variety of disaster spread simulation. [ABSTRACT FROM AUTHOR]

The model-free adaptive controller (MFAC) for continuous rotary electro-hydraulic servo motor was proposed to deal with uncertainties such as friction, leakage and noise. The model of electro-hydraulic servo motor system was replaced by universal model, and the structure adaptive control and parameter adaptive control were combined, and MFAC controller of the motor system was designed by using the input and output data of the system to realize the low speed and tracking control of the motor system. It is proved by simulation and experiment that MFAC controller effectively improves the low-speed stability and anti-interference ability of electro-hydraulic servo system compared with traditional PID control, and MFAC controller widens the frequency response of the system and realizes the precise control of continuous rotary motor servo system.

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Various radiobiological models have been proposed to describe the clonogenic cell survival after radiation. Least square model fitting to match experimental survival data can be tedious and sometimes difficult for complex models with multiple parameters. In this work, a random sampling method is developed to optimize the model parameters automatically to achieve best fitting with the experimental data. A computer program is developed to read the experimental data and to calculate the cell survival fractions based on a given mathematical model. Model parameters are randomly sampled, and the model predictions are compared with the experimental data. The mean square error (MSE) is used as an objective function to drive the iterative process. The goodness-of-fit of the linear quadratic (LQ), multitarget (MT), universal survival curves (USC) and multimode (MM) model was compared between the new method and previous studies for melanoma and non–small-cell lung cancer (NSCLC) cell lines. Good fitting was obtained for the MM model with the NSCLC data (MSE = 0.0005), which was better than the fits to the LQ, MT and USC models (MSE = 0.0019, 0.0082, 0.0024, respectively). The parameters used for the LQ, MT and USC models were α = 0.33Gy, α/β = 10Gy, D 0 = 1.25Gy, n = 4.22 and D T = 6.2Gy. The parameters for the MM model (n = 4) were D 1 = 3.0Gy, D 2 = 8.27Gy, and D 3 = 2.93Gy and D 4 = 10.6Gy. It is concluded that the random sampling method provides a useful tool for the parameterization of radiobiological models for radiation research and clinical applications. • A random sampling method has been used for radiobiological modeling. • The new method can derive complex model parameters accurately and efficiently. • The method has been tested for 4 radiobiological modes using realistic clinical data. • The fitting accuracy depends on the dose range used and model's flexibility. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we present a functional model theorem for completely non-coisometric n-tuples of operators in the noncommutative variety V f , φ , I ( H ) $\mathcal{V}_{f,\varphi,\mathcal{I}}(\mathcal{H})$ in terms of constrained characteristic functions. As an application, we prove that the constrained characteristic function is a complete unitary invariant for this class of elements, which can be viewed as the noncommutative analogue of the classical Sz.-Nagy–Foiaş functional model for completely nonunitary contractions. On the other hand, we provide a Sarason-type commutant lifting theorem. Applying this result, we solve the Nevanlinna–Pick-type interpolation problem in our setting. Moreover, we also obtain a Beurling-type characterization of the joint invariant subspaces under the operators B 1 , … , B n $B_{1},\ldots,B_{n}$ , where the n-tuple ( B 1 , … , B n ) $(B_{1},\ldots,B_{n})$ is the universal model associated with the abstract noncommutative variety V f , φ , I $\mathcal{V}_{f,\varphi,\mathcal{I}}$ .

Copyright of Journal of China University of Petroleum is the property of China University of Petroleum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The transportation of liquefied natural gas (LNG) is a crucial aspect of global energy application and security. However, there are still some challenges in liquefaction. This study establishes systematic experiments to investigate the condensation two-phase flow and heat transfer process of hydrocarbon-mixture energy (methane/ethane/propane/isobutane) in a spiral tube. The main influencing parameters, including mass flux (200–560 kg/(m2·s)), operating pressure (2–4 MPa), and vapor quality (0–1) on the heat transfer intensity and frictional pressure drop were analyzed. Different two-phase flow patterns were observed and categorized them as bubble flow, intermittent flow, stratified-wavy flow, and annular flow. For bubble flow and intermittent flow, vapor quality is found to remarkably affect the heat transfer; regarding stratified-wavy flow and annular flow, gravitational force and inertia force are found to prominently influence the heat transfer, respectively. Additionally, a newly universal model includes split flow patterns mode (SFPM) and the general mode (GM) has been proposed, which is with high-precision for describing the condensation heat transfer coefficients of different flow patterns. Furthermore, the analytical results show the SFPM's root mean square error and mean absolute relative deviation are 97.35 W/(m2·K) and 0.036. • The condensation flow and heat transfer characteristics of hydrocarbon-mixture energy are comprehensively studied. • Criterions of flow pattern based on Martinelli and modified Weber number are developed. • The heat transfer mechanisms for different flow patterns are provided. • A universal model of heat transfer has been established for entire condensation processes (determination coefficient >0.95). [ABSTRACT FROM AUTHOR]

• First presented a universal canopy gap fraction (GF) model for forests with various tree distributions. • Accuracy of canopy GF at off-nadir is significantly improved by the new model. • Universality and accuracy of the universal model are validated by a ray-tracing method. • Universal model form the backbone of the development of a potentially universal canopy reflectance model. An accurate estimation of forest canopy gap fraction (GF) is a prerequisite for remote sensing retrievals of several associated canopy parameters e.g. leaf area index, fAPAR (fraction of photosynthetically active radiation absorbed by the canopy), clumping index, etc. A universal canopy GF model for forests is required for various tree distribution patterns on flat and slopping terrains, yet existing models so far do not possess all these abilities simultaneously. For example, the Neyman type-A model, the Poisson model, and the hypergeometric model are suitable only to forests with clumped, random, and regular tree distributions, respectively. In this regard, the suite of Nilson's canopy GF models developed for forests with various tree distributions have the potential to become universal models. For this purpose, this study attempts to overcome the following limitations of these models to make them be true universally applicable: (1) canopy GF calculated by the Nilson's models is mostly accurate for various tree distributions at nadir; whereas at it is either underestimated for clumped tree distributions or overestimated for regular tree distributions at off-nadir; and (2) Nilson's models were developed for flat terrains and untested for sloping terrains. Herein, two Nilson's models are modified by expanding the calculation of overlaps among crowns (OAC) at nadir to the whole hemispherical space. The results show that all canopy GF simulations in the new models (New91 and New99) show higher consistency with ray-tracing results than those in original Nilson's models in all directions, highlighting the need to consider directional OAC. The modified models (especially for New99) are validated in two RAMI forest stands and a Saihanba forest stand: the relative error in canopy GF between the modified models and a ray-tracing model is less than 10 % in all forest stands. The modified models (especially New99) are suitable for various tree distributions on flat and slopping terrains and therefore increased the universality of the original Nilson's models suitable for a wide-range of remote sensing applications. New99 can be deemed as a universal canopy GF model for forests with various tree distributions. [ABSTRACT FROM AUTHOR]

We prove that the variety of nuclear implicative semilattices is locally finite, thus generalizing Diego's Theorem. The key ingredients of our proof include the coloring technique and construction of universal models from modal logic. For this we develop duality theory for finite nuclear implicative semilattices, generalizing Köhler duality. We prove that our main result remains true for bounded nuclear implicative semilattices, give an alternative proof of Diego's Theorem, and provide an explicit description of the free cyclic nuclear implicative semilattice. [ABSTRACT FROM AUTHOR]

The universal test system model, which permits to structurally describe test automation tasks aimed at the efficient use of the existing test toolkits and the creation of new ones, is considered.

In this paper, we present a functional model theorem for completely non-coisometric n-tuples of operators in the noncommutative variety V f , φ , I (H) in terms of constrained characteristic functions. As an application, we prove that the constrained characteristic function is a complete unitary invariant for this class of elements, which can be viewed as the noncommutative analogue of the classical Sz.-Nagy–Foiaş functional model for completely nonunitary contractions. On the other hand, we provide a Sarason-type commutant lifting theorem. Applying this result, we solve the Nevanlinna–Pick-type interpolation problem in our setting. Moreover, we also obtain a Beurling-type characterization of the joint invariant subspaces under the operators B 1 , ... , B n , where the n-tuple (B 1 , ... , B n) is the universal model associated with the abstract noncommutative variety V f , φ , I . [ABSTRACT FROM AUTHOR]

In this study, a non-destructive method using visible/near infrared (Vis/NIR) spectroscopy was investigated to predict the soluble solids content (SSC) of intact melons (Cucumis melo L.) cv. 'Manao', 'Jinhongbao', 'Xizhoumi'. A set of 360 samples (120 melons of each cultivar) was used to develop the calibration model, and two location (stylar-end and equatorial locations) models were investigated independently. The samples' spectra were obtained by a portable Vis/NIR photo-diode array spectrometer operated in reflectance mode. Multiplicative scatter correction (MSC), first derivative and Savizky-Golay (SG) smoothing in turn were applied to the obtained spectra. The region from 750 to 950 nm was selected to develop NIR models combined with the partial least squares (PLS) regression method. The results indicated that the stylar-end of the intact melon was the proper location to evaluate the SSC in the intact melon due to its suitable and exclusive physiological structure. A competitive adaptive reweighted sampling (CARS) algorithm was used to select effective wavelengths. Results showed that the CARS algorithm had great potential for simplifying the variables. Furthermore, another 195 samples were used for external prediction to evaluate the CARS-PLS model's accuracy and stability, which resulted in a high determination coefficient (R 2 p = 0.83) and a low root mean square error (RMSEP = 0.73 ºBrix). Image 1 • A universal NIR model for SSC testing among three cultivars was examined. • Some spectral pre-treatments were helpful to develop a universal model. • Stylar-end proved more appropriate to predict SSC of three cultivars melons. • CARS algorithm reliable for effective wavelengths selection for universal PLS model. [ABSTRACT FROM AUTHOR]

The quest for stable gas‐phase anions in highly negative charge states has been a great challenge. While multiply charged anions are stabilized in solids and liquids by compensating cations and solvation cells, respectively, stable anions containing less than a hundred atoms in the gas phase and capable of carrying charge beyond −3 is unknown. Here, we report the discovery of thermodynamically stable tetra‐ and penta‐anions, containing less than 50 and 80 atoms, respectively, in the gas phase. A universal model is developed that explains their stability in terms of the synergy between closed shell, high electron affinity, and size and predicts new highly‐charged anions by using the known charged clusters as building blocks. Synthesis of these species can open a new chapter in materials chemistry. [ABSTRACT FROM AUTHOR]

Using a cross-regional analysis of China, this article shows that the China model view is factually false and the universal model view is factually true. It is the marketization and development of non-state sectors, rather than the strong power of government and the state sector, that have driven the Chinese economy to grow fast and to be increasingly innovative. If China wants to sustain its economic performance, it must stay on the way to continuing marketization. Otherwise, China will fall into stagnation. [ABSTRACT FROM AUTHOR]

Although the importance of people and institutions has been highlighted in multinational enterprise studies, the association between people, institutions, and the internationalization of small to medium‐sized enterprise (SMEs) is an underexplored issue from the context of a small developing country. We examine theories subsumed under the Universal Model of human resource management (HRM) onto SMEs to study the hypothesized people and institutionally orientated barriers posed to SMEs' internationalization. Using quantitative analysis, the impacts of the barriers on internationalization are highlighted with particular attention to employer attractiveness. Following extant literature review, this study has used primary data collected through questionnaires from 212 Bangladeshi SMEs. We developed and validated the partial least square‐based structural equation model (PLS‐SEM) to assess the impacts and successfully framed people versus institutional barriers as a second‐order hierarchical reflective model, which has not been done previously. Given their marginal significance over institutions, people‐oriented cultural barriers should be included as an extension of the Universal Model to study SME internationalization. [ABSTRACT FROM AUTHOR]

Reliability evaluation by using probabilistic computational models has become an important research field in modern digital designs. Based on the profound understanding of different reliability evaluation methods, this paper proposes a universal model for signal probability and reliability analysis of logic circuits. The proposed Signal Probability Level Matrix (SPLM) provides us with the reliability and signal probability of the entire circuit as well as individual outputs. We can deal with SPLM very flexibly depending on different applications and design constraints. The accuracy and efficiency of the proposed model have been proved and verified by representative circuits in literatures. Furthermore, the proposed model is particularly useful in reliability assessment in cascade-structure circuits such as ripple carry adders. [ABSTRACT FROM AUTHOR]

The accuracy of quantitative models for near-infrared (NIR) spectroscopy is dependent upon calibration samples with concentration variations. Conventional sample-collection methods have shortcomings (especially time-consumption), which creates a “bottleneck” in the application of NIR models for Process Analytical Technology (PAT) control. We undertook a study to solve the problem of sample collection for construction of NIR quantitative models. Amoxicillin and potassium clavulanate oral dosage forms (ODFs) were used as examples. The aim of this study was to find an approach to construct NIR quantitative models rapidly using a NIR spectral library based on the idea of a universal model. The NIR spectral library of amoxicillin and potassium clavulanate ODFs was defined and comprised the spectra of 377 batches of samples produced by 26 domestic pharmaceutical companies, including tablets, dispersible tablets, chewable tablets, oral suspensions, and granules. The correlation coefficient (rT) was used to indicate the similarities of the spectra. The calibration sets of samples were selected from a spectral library according to the median rT of the samples to be analyzed. The rT of the samples selected was close to the median rT. The difference in rT of these samples was 1.0–1.5%. We concluded that sample selection was not a problem when constructing NIR quantitative models using a spectral library compared with conventional methods of determining universal models. Sample spectra with a suitable concentration range in NIR models were collected rapidly. In addition, the models constructed through this method were targeted readily.

This paper presents the development, testing and validation of a novel generic type universal model consisting of a set of sine and cosine harmonics in the temporal and spatial domain suitably parameterized for the prediction of the mean expected global solar radiation H(n,φ) on the horizontal for a day, n, at any latitude φ. Its prediction power is further enhanced with the introduction of a correction term for the site altitude taking into account the φ dependent atmospheric height. Solar radiation data from 53 stations around the earth were obtained from GEBA database to train the model. H(n,φ) is expressed by a Fourier series of compact form with the zero frequency component dependent on φ providing the main spatial dependence and two n dependent harmonics in the form of cosine functions giving the time dependence. The φ dependent model parameters follow symmetry rules and are expressed by Fourier series up to the 3rd order harmonic. The 3D spatiotemporal profile of the model is in agreement to the extraterrestrial one. The model was validated using GEBA data from additional 28 sites and compared with NASA, PVGIS and SoDa data, showing the robustness, reliability and prediction accuracy of the proposed model. [ABSTRACT FROM AUTHOR]

Abstract: A new set of quantitative models of colour emotion and colour harmony were developed in this study using psychophysical data collected from 12 regions in the world, including Argentina, China, France, Germany, Hungary, Iran, Japan, Spain, Sweden, Taiwan, Thailand, and the UK. These data have previously been published in journals or conferences (for details see Tables and ). For colour emotion, three new models were derived, showing satisfactory predictive performance in terms of an average correlation coefficient of 0.78 for “warm/cool”, 0.80 for “heavy/light” and 0.81 for “active/passive”. The new colour harmony model also had satisfactory predictive performance, with an average correlation coefficient of 0.72. Principal component analysis shows that the common colour harmony principles, including hue similarity, chroma similarity, lightness difference and high lightness principles, were partly agreed by observers of the same region. The findings suggest that it is feasible to develop universal models of colour emotion and colour harmony, and that the former was found to be relatively more culture‐independent than the latter. [ABSTRACT FROM AUTHOR]

Copyright of Society: Chinese Journal of Sociology / Shehui is the property of Society: Chinese Journal of Sociology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research of a disaster chain can help to determine the mechanism of disaster and the mechanism of mutual transformation between disasters; but at present, a unified and comprehensive modeling mechanism for the disaster chain evolution process has not been formed. Based on hierarchical modeling theory, a top-down refinement method for modeling the complex disaster chain evolution process was proposed in this article—the Spatio-temporal evolution process Multi-level description Framework for a Disaster Chain (STMFDC). The semantic description of the disaster chain is realized at the phenomenon level, changing element level, abstract semantics association level, and resource implementation level. In the spatio-temporal semantic constraint, combining the data integration methods, the evolution process model was also built to analyze the catastrophic process of the disaster chain. Finally, the mining subsidence disaster chain caused by human engineering activity was taken as an example to analyze the evolution process of a subsidence disaster chain based on the STMFDC to verify its generality. The study will thus form a new way of researching a disaster chain by building off the STMFDC approach. [ABSTRACT FROM AUTHOR]

A unified theoretical model applicable to different types of Triboelectric Nanogenerators (TENGs) is presented based on Maxwell's equations, which fully explains the working principles of a majority of TENG types. This new model utilizes the distance-dependent electric field (DDEF) concept to derive a universal theoretical platform for all vertical charge polarization TENG types which overcomes the inaccuracies of the classical theoretical models as well as the limitations of the existing electric field-based model. The theoretical results show excellent agreement with experimental TENGs for all working modes, providing an improved capability of predicting the influence of different device parameters on the output behaviour. Finally, the output performances of different TENG types are compared. This work, for the first time, presents a unified framework of analytical equations for different TENG working modes, leading to an in-depth understanding of their working principles, which in turn enables more precise design and construction of efficient energy harvesters. [ABSTRACT FROM AUTHOR]

Polynomial model adopted for the moisture content influence to the drying rate of non-hygroscopic products like the pozzolana presented some limits. This model was not universal and has diverged whether moisture content different to the appropriate experiment values has been used. Thus, a new exponential model based on the inverse of moisture content and respecting to the imposed boundary conditions has been proposed. Model parameters were determined using the least square approximation method of Newton-Marquart. The predicted temporal variations of moisture content were provided from the Runge-Kutta fourth order integration scheme computed on the new model of drying rate. Moreover, two-way ANOVA method was performed on data analysis, at the parameters statistical significance and in residual analysis for the model fit quality. Model validations were done by comparisons among theoretical and experimental values and between predicted and polynomial models. Comparisons showed a good agreement with highest R² and lowest reduced chi-square, MBE, RMSE, and MAPE. [ABSTRACT FROM AUTHOR]